Transport System Models and Big Data: Zoning and Graph Building with Traditional Surveys, FCD and GIS

The paper deals with the integration of data provided from traditional transport surveys (small data) with big data, provided from Information and Communication Technology (ICT), in building Transport System Models (TSMs). Big data are used to observe historical mobility patterns and transport facilities and services, but they are not able to assess ex-ante effects of planned interventions and policies. To overcome these limitations, TSMs can be specified, calibrated and validated with small data, but they are expensive to obtain. The paper proposes a procedure to increase the benefits of TSMs’ building in forecasting capabilities, on one side; and limiting the costs connected to traditional surveys thanks to the availability of big data, on the other side. Small data (e.g., census data) are enriched with Floating Car Data (FCD). At the current stage, the procedure focuses on two specific elements of TSMs: zoning and graph building. These processes are both executed considering the estimated values of an intensity function of FCDs, consistently with traditional methods based on small data. The data-fusion of small and big data, operated with a Geographic Information System (GIS) tool, in a real extra-urban context is presented in order to validate the proposed procedure.

[1]  J. Rijsdijk,et al.  Improving A Priori Demand Estimates Transport Models using Mobile Phone Data: A Rotterdam-Region Case , 2016 .

[2]  Lidia P. Kostyniuk,et al.  Using GPS Data to Understand Driving Behavior , 2008 .

[3]  Dragan Pamučar,et al.  VEHICLE ROUTE SELECTION WITH AN ADAPTIVE NEURO FUZZY INFERENCE SYSTEM IN UNCERTAINTY CONDITIONS , 2018 .

[4]  Chilà Giovanna,et al.  Transport models and intelligent transportation system to support urban evacuation planning process , 2016 .

[5]  Francis Oloo,et al.  Mapping Rural Road Networks from Global Positioning System (GPS) Trajectories of Motorcycle Taxis in Sigomre Area, Siaya County, Kenya , 2018, ISPRS Int. J. Geo Inf..

[6]  Antonio Iera,et al.  An experimental station for real-time traffic monitoring on a urban road , 2002, Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems.

[7]  Alexander Erath,et al.  Transport modelling in the age of big data , 2017 .

[8]  Helena Beatriz Bettella Cybis,et al.  Influence of GPS and Self-reported Data in Travel Demand Models , 2014 .

[9]  Yu Liu,et al.  The promises of big data and small data for travel behavior (aka human mobility) analysis , 2016, Transportation research. Part C, Emerging technologies.

[10]  Dragan Pamučar,et al.  Transport spatial model for the definition of green routes for city logistics centers , 2016 .

[11]  Agostino Nuzzolo,et al.  Urban freight transport policies in Rome: lessons learned and the road ahead , 2015 .

[12]  Giuseppe Musolino,et al.  Signal Setting Optimization on Urban Road Transport Networks: The Case of Emergency Evacuation , 2015 .

[13]  Marta C. González,et al.  The path most traveled: Travel demand estimation using big data resources , 2015, Transportation Research Part C: Emerging Technologies.

[14]  Diansheng Guo,et al.  A graph-based approach to vehicle trajectory analysis , 2010, J. Locat. Based Serv..

[15]  Marcela Munizaga,et al.  Transport survey methods - in the era of big data facing new and old challenges , 2018 .

[16]  Bin Jiang,et al.  Geospatial analysis requires a different way of thinking: the problem of spatial heterogeneity , 2015 .

[17]  Antonino Vitetta,et al.  From GREen ENErgy to green LOGistic : A joint analysis of energy , accessibility and mobility , 2018 .

[18]  Yoshihide Sekimoto,et al.  Estimation of Hourly Link Population and Flow Directions from Mobile CDR , 2018, ISPRS Int. J. Geo Inf..

[19]  Antonino Vitetta,et al.  Passenger Mobility in a Discontinuous Space: Modelling Access/Egress to Maritime Barrier in a Case Study , 2018, Journal of Advanced Transportation.

[20]  Beniamino Murgante,et al.  Kernel Density Estimation Methods for a Geostatistical Approach in Seismic Risk Analysis: The Case Study of Potenza Hilltop Town (Southern Italy) , 2008, ICCSA.

[21]  Vincenzo Gallelli,et al.  Transport and traffic management by micro simulation models: operational use and performance of roundabouts , 2012 .

[22]  Giuseppe Musolino,et al.  Experimental analysis of different simulation models for motorway traffic flow , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[23]  Bin Jiang Spatial Heterogeneity, Scale, Data Character, and Sustainable Transport in the Big Data Era , 2018, ISPRS Int. J. Geo Inf..

[24]  Karin Baier,et al.  Transportation Systems Analysis Models And Applications , 2016 .

[25]  Francesco Russo,et al.  Safety of Users in Road Evacuation: Planning Internal Processes and Guidelines , 2007 .